Doctoral Dissertation Research: Examining Diet, Mobility, and Social Dynamics Using a Multi Isotopic Approach and GIS

该奖项全部或部分由《2021年美国救援计划法案》（公法117-2）资助。纵观人类历史，许多因素影响着个人的流动性和饮食，在许多情况下，饮食习惯随着社会地位和信仰体系等其他因素的变化而分化。本博士论文采用生物考古研究方法，将骨骼分析与环境和文化方面结合起来，研究人群和个人层面的饮食和埋葬方式，研究社会重组如何影响过去人类群体中更广泛的社区。探索生前的饮食选择和死后的地位，有助于了解食物和埋葬习俗如何与社会角色相关并重申社会角色。该项目的更广泛影响包括培养一名女研究生，加强国际科研合作，以及向公众传播研究成果。该项目探讨了信仰体系和社会地位与饮食、起源和流动性的关系。研究人员将这些动态与年龄、性别和社会地位联系在一起，对来自同一社区的两个分别代表宗教精英和非精英个人的骨骼样本进行了研究。该研究考察了是否存在基于潜在地位差异的饮食差异，以及是否可以确定非本地个体的原籍地。该项目采用生物化学、地理空间和统计学相结合的方法，包括四种同位素判别法（碳、氮、氧和锶）、贝叶斯FRUITS混合模型和研究区域的地理空间分析。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). Throughout human history, many factors have influenced an individual’s mobility and diet, and in many cases, dietary practices have diverged alongside changes in other factors such as social status and belief systems. Using bioarchaeological research methods that combine skeletal analyses with aspects of environment and culture to examine diet and burial style at the population and individual levels, this doctoral dissertation research examines how social reorganization affected a broader community in past human populations. Exploring dietary choices during life and status after death advances knowledge about how food and burial practices relate to and reaffirm social roles. Broader impacts of the project include STEM training of a female graduate student, strengthening of international scientific research collaborations, and dissemination of research to the public.The project explores the relationship of belief systems and social status to diet, origins, and mobility. The investigators consider these dynamics in conjunction with age, sex, and status for two skeletal samples representing religious elites and non-elite individuals, respectively, from the same community. The research examines whether there are dietary differences based on potential status differences and whether place of origin can be identified for non-local individuals. The project utilizes a combination of biochemical, geospatial, and statistical methods, including four isotopic discriminants (carbon, nitrogen, oxygen, and strontium), the Bayesian FRUITS mixing model, and geospatial analysis of the study region.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.